Transcriptional biomarkers of toxicity - powerful tools or random noise? : An applied perspective from studies on bivalves

Sammanfattning: Aquatic organisms are constantly at risk of being exposed to potentially harmful chemical compounds of natural or anthropogenic origin. Biological life can for instance respond to chemical stressors by changes in gene expression, and thus, certain gene transcripts can potentially function as biomarkers, i.e. early warnings, of toxicity and chemical stress. A major challenge for biomarker application is the extrapolation of transcriptional data to potential effects at the organism level or above. Importantly, successful biomarker use also requires basal understanding of how to distinguish actual responses from background noise. The aim of this thesis is, based on response magnitude and variation, to evaluate the biomarker potential in a set of putative transcriptional biomarkers of general toxicity and chemical stress.Specifically, I addressed a selection of six transcripts involved in cytoprotection and oxidative stress: catalase (cat), glutathione-S-transferase (gst), heat shock proteins 70 and 90 (hsp70, hsp90), metallothionein (mt) and superoxide dismutase (sod). Moreover, I used metal exposures to serve as a proxy for general chemical stress, and due to their ecological relevance and nature as sedentary filter-feeders, I used bivalves as study organisms.In a series of experiments, I tested transcriptional responses in the freshwater duck mussel, Anodonta anatina, exposed to copper or an industrial waste-water effluent, to address response robustness and sensitivity, and potential controlled (e.g. exposure concentration) and random (e.g. gravidness) sources of variation. In addition, I performed a systematic review and meta-analysis on transcriptional responses in metal exposed bivalves to (1) evaluate what responses to expect from arbitrary metal exposures, (2) assess the influence from metal concentration (expressed as toxic unit), exposure time and analyzed tissue, and (3) address potential impacts from publication bias in the scientific literature.Response magnitudes were generally small in relationship to the observed variation, both for A. anatina and bivalves in general. The expected response to an arbitrary metal exposure would generally be close to zero, based on both experimental observations and on the estimated impact from publication bias. Although many of the transcripts demonstrated concentration-response relationships, large background noise might in practice obscure the small responses even at relatively high exposures. As demonstrated in A. anatina under copper exposure, this can be the case already for single species under high resolution exposures to single pollutants. As demonstrated by the meta-regression, this problem can only be expected to increase further upon extrapolation between different species and exposure scenarios, due to increasing heterogeneity and random variation. Similar patterns can also be expected for time-dependent response variation, although the meta-regression revealed a general trend of slightly increasing response magnitude with increasing exposure times.In A. anatina, gravidness was identified as a source of random variability that can potentially affect the baseline of most assessed biomarkers, particularly when quantified in gills. Response magnitudes and variability in this species were generally similar for selected transcripts as for two biochemical biomarkers included for comparison (AChE, GST), suggesting that the transcripts might not capture early warnings more efficiently than other molecular endpoints that are more toxicologically relevant. Overall, high concentrations and long exposure durations presumably increase the likelihood of a detectable transcriptional response, but not to an extent that justifies universal application as biomarkers of general toxicity and chemical stress. Consequently, without a strictly defined and validated application, this approach on its own appears unlikely to be successful for future environmental risk assessment and monitoring. Ultimately, efficient use of transcriptional biomarkers might require additional implementation of complementary approaches offered by current molecular techniques.